We learn the following operators: dilation, erosion, opening, closing, black top-hat, and white top-hat. The 3 SEs used can be seen on table REF . For erosion and dilation on MNIST, we use smaller SEs of size \(5 \times 5\) . Else for all other operations, SEs are of size \(7 \times 7\) .
The experimental protocol is as follows: let \(\gamma \)  be one of these morphological operators. The input-output couples are \(\lbrace (x_i, \gamma (x_i)) ~|~ x_i \in \text{dataset}\rbrace \) . The hyperparameters are the loss used, the learning rate, and the batch size. For each result, see the code for the hyperparameters used. We measure the DICE score [1]} between the predictions and targets.
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